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Aczel B, Szaszi B, Nilsonne G, van den Akker OR, Albers CJ, van Assen MALM, Bastiaansen JA, Benjamin D, Boehm U, Botvinik-Nezer R, Bringmann LF, Busch NA, Caruyer E, Cataldo AM, Cowan N, Delios A, van Dongen NNN, Donkin C, van Doorn JB, Dreber A, Dutilh G, Egan GF, Gernsbacher MA, Hoekstra R, Hoffmann S, Holzmeister F, Huber J, Johannesson M, Jonas KJ, Kindel AT, Kirchler M, Kunkels YK, Lindsay DS, Mangin JF, Matzke D, Munafò MR, Newell BR, Nosek BA, Poldrack RA, van Ravenzwaaij D, Rieskamp J, Salganik MJ, Sarafoglou A, Schonberg T, Schweinsberg M, Shanks D, Silberzahn R, Simons DJ, Spellman BA, St-Jean S, Starns JJ, Uhlmann EL, Wicherts J, Wagenmakers EJ. Consensus-based guidance for conducting and reporting multi-analyst studies. eLife 2021; 10:e72185. [PMID: 34751133 PMCID: PMC8626083 DOI: 10.7554/elife.72185] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 11/07/2021] [Indexed: 11/13/2022] Open
Abstract
Any large dataset can be analyzed in a number of ways, and it is possible that the use of different analysis strategies will lead to different results and conclusions. One way to assess whether the results obtained depend on the analysis strategy chosen is to employ multiple analysts and leave each of them free to follow their own approach. Here, we present consensus-based guidance for conducting and reporting such multi-analyst studies, and we discuss how broader adoption of the multi-analyst approach has the potential to strengthen the robustness of results and conclusions obtained from analyses of datasets in basic and applied research.
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Affiliation(s)
| | | | - Gustav Nilsonne
- Karolinska InstitutetStockholmSweden
- Stockholm UniversityStockholmSweden
| | | | | | | | - Jojanneke A Bastiaansen
- University Medical Center Groningen, University of GroningenGroningenNetherlands
- Friesland Mental Health Care ServicesLeeuwardenNetherlands
| | - Daniel Benjamin
- University of California Los AngelesLos AngelesUnited States
- National Bureau of Economic ResearchCambridgeUnited States
| | - Udo Boehm
- University of AmsterdamAmsterdamNetherlands
| | | | | | | | | | - Andrea M Cataldo
- McLean HospitalBelmontUnited States
- Harvard Medical SchoolBostonUnited States
| | | | | | | | | | | | - Anna Dreber
- Stockholm School of EconomicsStockholmSweden
- University of InnsbruckInnsbruckAustria
| | | | | | | | | | | | | | | | | | | | | | | | - Yoram K Kunkels
- University Medical Center Groningen, University of GroningenGroningenNetherlands
| | | | | | | | | | | | - Brian A Nosek
- Center for Open ScienceCharlottesvilleUnited States
- University of VirginiaCharlottesvilleUnited States
| | | | | | | | | | | | | | | | | | | | | | | | - Samuel St-Jean
- University of AlbertaEdmontonCanada
- Lund UniversityLundUnited States
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2
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Schweinsberg M, Feldman M, Staub N, van den Akker OR, van Aert RC, van Assen MA, Liu Y, Althoff T, Heer J, Kale A, Mohamed Z, Amireh H, Venkatesh Prasad V, Bernstein A, Robinson E, Snellman K, Amy Sommer S, Otner SM, Robinson D, Madan N, Silberzahn R, Goldstein P, Tierney W, Murase T, Mandl B, Viganola D, Strobl C, Schaumans CB, Kelchtermans S, Naseeb C, Mason Garrison S, Yarkoni T, Richard Chan C, Adie P, Alaburda P, Albers C, Alspaugh S, Alstott J, Nelson AA, Ariño de la Rubia E, Arzi A, Bahník Š, Baik J, Winther Balling L, Banker S, AA Baranger D, Barr DJ, Barros-Rivera B, Bauer M, Blaise E, Boelen L, Bohle Carbonell K, Briers RA, Burkhard O, Canela MA, Castrillo L, Catlett T, Chen O, Clark M, Cohn B, Coppock A, Cugueró-Escofet N, Curran PG, Cyrus-Lai W, Dai D, Valentino Dalla Riva G, Danielsson H, Russo RDF, de Silva N, Derungs C, Dondelinger F, Duarte de Souza C, Tyson Dube B, Dubova M, Mark Dunn B, Adriaan Edelsbrunner P, Finley S, Fox N, Gnambs T, Gong Y, Grand E, Greenawalt B, Han D, Hanel PH, Hong AB, Hood D, Hsueh J, Huang L, Hui KN, Hultman KA, Javaid A, Ji Jiang L, Jong J, Kamdar J, Kane D, Kappler G, Kaszubowski E, Kavanagh CM, Khabsa M, Kleinberg B, Kouros J, Krause H, Krypotos AM, Lavbič D, Ling Lee R, Leffel T, Yang Lim W, Liverani S, Loh B, Lønsmann D, Wei Low J, Lu A, MacDonald K, Madan CR, Hjorth Madsen L, Maimone C, Mangold A, Marshall A, Ester Matskewich H, Mavon K, McLain KL, McNamara AA, McNeill M, Mertens U, Miller D, Moore B, Moore A, Nantz E, Nasrullah Z, Nejkovic V, Nell CS, Arthur Nelson A, Nilsonne G, Nolan R, O'Brien CE, O'Neill P, O'Shea K, Olita T, Otterbacher J, Palsetia D, Pereira B, Pozdniakov I, Protzko J, Reyt JN, Riddle T, (Akmal) Ridhwan Omar Ali A, Ropovik I, Rosenberg JM, Rothen S, Schulte-Mecklenbeck M, Sharma N, Shotwell G, Skarzynski M, Stedden W, Stodden V, Stoffel MA, Stoltzman S, Subbaiah S, Tatman R, Thibodeau PH, Tomkins S, Valdivia A, Druijff-van de Woestijne GB, Viana L, Villesèche F, Duncan Wadsworth W, Wanders F, Watts K, Wells JD, Whelpley CE, Won A, Wu L, Yip A, Youngflesh C, Yu JC, Zandian A, Zhang L, Zibman C, Luis Uhlmann E. Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis. Organizational Behavior and Human Decision Processes 2021. [DOI: 10.1016/j.obhdp.2021.02.003] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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Rohrer JM, Tierney W, Uhlmann EL, DeBruine LM, Heyman T, Jones B, Schmukle SC, Silberzahn R, Willén RM, Carlsson R, Lucas RE, Strand J, Vazire S, Witt JK, Zentall TR, Chabris CF, Yarkoni T. Putting the Self in Self-Correction: Findings From the Loss-of-Confidence Project. Perspect Psychol Sci 2021; 16:1255-1269. [PMID: 33645334 PMCID: PMC8564260 DOI: 10.1177/1745691620964106] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Science is often perceived to be a self-correcting enterprise. In principle, the
assessment of scientific claims is supposed to proceed in a cumulative fashion,
with the reigning theories of the day progressively approximating truth more
accurately over time. In practice, however, cumulative self-correction tends to
proceed less efficiently than one might naively suppose. Far from evaluating new
evidence dispassionately and infallibly, individual scientists often cling
stubbornly to prior findings. Here we explore the dynamics of scientific
self-correction at an individual rather than collective level. In 13 written
statements, researchers from diverse branches of psychology share why and how
they have lost confidence in one of their own published findings. We
qualitatively characterize these disclosures and explore their implications. A
cross-disciplinary survey suggests that such loss-of-confidence sentiments are
surprisingly common among members of the broader scientific population yet
rarely become part of the public record. We argue that removing barriers to
self-correction at the individual level is imperative if the scientific
community as a whole is to achieve the ideal of efficient self-correction.
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Affiliation(s)
- Julia M Rohrer
- International Max Planck Research School on the Life Course, Max Planck Institute for Human Development, Berlin.,Department of Psychology, University of Leipzig
| | - Warren Tierney
- Department of Organizational Behavior, INSEAD, Singapore
| | - Eric L Uhlmann
- Department of Organizational Behavior, INSEAD, Singapore
| | - Lisa M DeBruine
- Institute of Neuroscience and Psychology, University of Glasgow
| | - Tom Heyman
- Laboratory of Experimental Psychology, KU Leuven.,Institute of Psychology, Leiden University
| | - Benedict Jones
- Institute of Neuroscience and Psychology, University of Glasgow
| | | | | | - Rebecca M Willén
- Institute for Globally Distributed Open Research and Education (IGDORE)
| | | | | | | | - Simine Vazire
- Melbourne School of Psychological Sciences, University of Melbourne
| | | | | | - Christopher F Chabris
- Autism and Developmental Medicine Institute, Geisinger Health System, Danville, Pennsylvania
| | - Tal Yarkoni
- Department of Psychology, University of Texas at Austin
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4
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Uhlmann EL, Ebersole CR, Chartier CR, Errington TM, Kidwell MC, Lai CK, McCarthy RJ, Riegelman A, Silberzahn R, Nosek BA. Scientific Utopia III: Crowdsourcing Science. Perspect Psychol Sci 2019; 14:711-733. [PMID: 31260639 DOI: 10.1177/1745691619850561] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Most scientific research is conducted by small teams of investigators who together formulate hypotheses, collect data, conduct analyses, and report novel findings. These teams operate independently as vertically integrated silos. Here we argue that scientific research that is horizontally distributed can provide substantial complementary value, aiming to maximize available resources, promote inclusiveness and transparency, and increase rigor and reliability. This alternative approach enables researchers to tackle ambitious projects that would not be possible under the standard model. Crowdsourced scientific initiatives vary in the degree of communication between project members from largely independent work curated by a coordination team to crowd collaboration on shared activities. The potential benefits and challenges of large-scale collaboration span the entire research process: ideation, study design, data collection, data analysis, reporting, and peer review. Complementing traditional small science with crowdsourced approaches can accelerate the progress of science and improve the quality of scientific research.
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Affiliation(s)
| | | | | | | | | | - Calvin K Lai
- 6 Department of Psychological and Brain Sciences, Washington University in St. Louis
| | - Randy J McCarthy
- 7 Center for the Study of Family Violence and Sexual Assault, Northern Illinois University
| | | | | | - Brian A Nosek
- 2 Department of Psychology, University of Virginia.,4 Center for Open Science, Charlottesville, Virginia
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5
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Silberzahn R, Uhlmann EL, Martin DP, Anselmi P, Aust F, Awtrey E, Bahník Š, Bai F, Bannard C, Bonnier E, Carlsson R, Cheung F, Christensen G, Clay R, Craig MA, Dalla Rosa A, Dam L, Evans MH, Flores Cervantes I, Fong N, Gamez-Djokic M, Glenz A, Gordon-McKeon S, Heaton TJ, Hederos K, Heene M, Hofelich Mohr AJ, Högden F, Hui K, Johannesson M, Kalodimos J, Kaszubowski E, Kennedy DM, Lei R, Lindsay TA, Liverani S, Madan CR, Molden D, Molleman E, Morey RD, Mulder LB, Nijstad BR, Pope NG, Pope B, Prenoveau JM, Rink F, Robusto E, Roderique H, Sandberg A, Schlüter E, Schönbrodt FD, Sherman MF, Sommer SA, Sotak K, Spain S, Spörlein C, Stafford T, Stefanutti L, Tauber S, Ullrich J, Vianello M, Wagenmakers EJ, Witkowiak M, Yoon S, Nosek BA. Many Analysts, One Data Set: Making Transparent How Variations in Analytic Choices Affect Results. Advances in Methods and Practices in Psychological Science 2018. [DOI: 10.1177/2515245917747646] [Citation(s) in RCA: 267] [Impact Index Per Article: 44.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Twenty-nine teams involving 61 analysts used the same data set to address the same research question: whether soccer referees are more likely to give red cards to dark-skin-toned players than to light-skin-toned players. Analytic approaches varied widely across the teams, and the estimated effect sizes ranged from 0.89 to 2.93 ( Mdn = 1.31) in odds-ratio units. Twenty teams (69%) found a statistically significant positive effect, and 9 teams (31%) did not observe a significant relationship. Overall, the 29 different analyses used 21 unique combinations of covariates. Neither analysts’ prior beliefs about the effect of interest nor their level of expertise readily explained the variation in the outcomes of the analyses. Peer ratings of the quality of the analyses also did not account for the variability. These findings suggest that significant variation in the results of analyses of complex data may be difficult to avoid, even by experts with honest intentions. Crowdsourcing data analysis, a strategy in which numerous research teams are recruited to simultaneously investigate the same research question, makes transparent how defensible, yet subjective, analytic choices influence research results.
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Affiliation(s)
- R. Silberzahn
- Organisational Behaviour, University of Sussex Business School
| | | | - D. P. Martin
- Department of Psychology, University of Virginia
| | - P. Anselmi
- Department of Philosophy, Sociology, Education and Applied Psychology, University of Padua
| | - F. Aust
- Department of Psychology, University of Cologne
| | - E. Awtrey
- Department of Management, University of Cincinnati
| | - Š. Bahník
- Department of Management, Faculty of Business Administration, University of Economics, Prague
| | - F. Bai
- Department of Management and Marketing, Hong Kong Polytechnic University
| | - C. Bannard
- Department of Psychology, University of Liverpool
| | - E. Bonnier
- Department of Economics, Stockholm School of Economics
| | - R. Carlsson
- Department of Psychology, Linnaeus University
| | - F. Cheung
- School of Public Health, University of Hong Kong
| | - G. Christensen
- Berkeley Institute for Data Science, University of California, Berkeley
| | - R. Clay
- Department of Psychology, College of Staten Island, City University of New York
| | - M. A. Craig
- Department of Psychology, New York University
| | - A. Dalla Rosa
- Department of Philosophy, Sociology, Education and Applied Psychology, University of Padua
| | - L. Dam
- Faculty of Economics and Business, University of Groningen
| | - M. H. Evans
- Division of Neuroscience and Experimental Psychology, University of Manchester
| | | | - N. Fong
- Department of Marketing and Supply Chain Management, Temple University
| | - M. Gamez-Djokic
- Department of Management and Organizations, Kellogg School of Management, Northwestern University
| | - A. Glenz
- Department of Psychology, University of Zurich
| | | | - T. J. Heaton
- School of Mathematics and Statistics, University of Sheffield
| | - K. Hederos
- Swedish Institute for Social Research (SOFI), Stockholm University
| | - M. Heene
- Department of Psychology, Ludwig-Maximilians-Universität München
| | | | - F. Högden
- Department of Psychology, University of Cologne
| | - K. Hui
- School of Management, Xiamen University
| | | | | | - E. Kaszubowski
- Department of Psychology, Federal University of Santa Catarina
| | - D. M. Kennedy
- School of Business, University of Washington Bothell
| | - R. Lei
- Department of Psychology, New York University
| | | | - S. Liverani
- School of Mathematical Sciences, Queen Mary University of London
| | - C. R. Madan
- School of Psychology, University of Nottingham
| | - D. Molden
- Department of Psychology, Northwestern University
| | - E. Molleman
- Faculty of Economics and Business, University of Groningen
| | | | - L. B. Mulder
- Faculty of Economics and Business, University of Groningen
| | - B. R. Nijstad
- Faculty of Economics and Business, University of Groningen
| | - N. G. Pope
- Department of Economics, University of Maryland
| | - B. Pope
- Department of Economics, Brigham Young University
| | | | - F. Rink
- Faculty of Economics and Business, University of Groningen
| | - E. Robusto
- Department of Philosophy, Sociology, Education and Applied Psychology, University of Padua
| | - H. Roderique
- Rotman School of Management, University of Toronto
| | - A. Sandberg
- Swedish Institute for Social Research (SOFI), Stockholm University
| | - E. Schlüter
- Department of Social Sciences and Cultural Studies, Institute of Sociology, Justus Liebig University, Giessen
| | - F. D. Schönbrodt
- Department of Psychology, Ludwig-Maximilians-Universität München
| | - M. F. Sherman
- Department of Psychology, Loyola University Maryland
| | | | - K. Sotak
- Department of Marketing and Management, SUNY Oswego
| | - S. Spain
- John Molson School of Business, Concordia University
| | - C. Spörlein
- Lehrstuhl für Soziologie, insb. Sozialstrukturanalyse, Otto-Friedrich-Universität Bamberg
| | - T. Stafford
- Department of Psychology, University of Sheffield
| | - L. Stefanutti
- Department of Philosophy, Sociology, Education and Applied Psychology, University of Padua
| | - S. Tauber
- Faculty of Economics and Business, University of Groningen
| | - J. Ullrich
- Department of Psychology, University of Zurich
| | - M. Vianello
- Department of Philosophy, Sociology, Education and Applied Psychology, University of Padua
| | | | | | - S. Yoon
- Department of Marketing and Supply Chain Management, Temple University
| | - B. A. Nosek
- Department of Psychology, University of Virginia
- Center for Open Science, Charlottesville, Virginia
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Abstract
Subsidiary-level change requires the alignment of subsidiary charters and capabilities. Yet, the mechanisms through which the alignment of charters and capabilities unfolds are not yet well understood. In this paper, we investigate alignment from the perspective of managerial coordination. Drawing on a longitudinal study of a global IT firm, we identify three coordination mechanisms (charter-, experience-, and interaction-based coordination). By tracing the shifts in these coordination mechanisms over time and by specifying the implications of each mechanism for capability level change, we explain how managerial coordination influences alignment via subsidiary level capability change as well as alignment via the potential renegotiation of charters. This also allows us to provide new insights into situations of misalignment by explaining that particular mechanisms of coordination may become a source of decoupling between subsidiary actions and HQ mandates and may also result in capability level inertia. Moreover, while prior research has already acknowledged the role of interaction-based coordination for capability level change we show how and why such a mechanism of coordination emerges.
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8
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Silberzahn R, Simonsohn U, Uhlmann EL. Matched-Names Analysis Reveals No Evidence of Name-Meaning Effects. Psychol Sci 2014; 25:1504-5. [DOI: 10.1177/0956797614533802] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2014] [Accepted: 04/02/2014] [Indexed: 11/15/2022] Open
Affiliation(s)
- Raphael Silberzahn
- Organisational Behaviour & Information Systems, Judge Business School, University of Cambridge
| | | | - Eric Luis Uhlmann
- Management and Human Resources
Department, HEC Paris School of Management
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9
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Abstract
In the field study reported here ( N = 222,924), we found that Germans with noble-sounding surnames, such as Kaiser (“emperor”), König (“king”), and Fürst (“prince”), more frequently hold managerial positions than Germans with last names that either refer to common everyday occupations, such as Koch (“cook”), Bauer (“farmer”), and Becker/Bäcker (“baker”), or do not refer to any social role. This phenomenon occurs despite the fact that noble-sounding surnames never indicated that the person actually held a noble title. Because of basic properties of associative cognition, the status linked to a name may spill over to its bearer and influence his or her occupational outcomes.
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Affiliation(s)
- Raphael Silberzahn
- Organizational Behaviour & Information Systems, Judge Business School, University of Cambridge
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